Director of QA

About the Company

We are a fast-growing, mission-driven healthcare technology company building modern software for organizations that serve large and diverse populations across the U.S.

Our platform helps healthcare and community-focused organizations improve engagement, streamline workflows, surface important insights, and coordinate services more effectively. By combining automation, data, and user-centered product design, we help our customers operate more efficiently and deliver better outcomes.

We are in a high-growth stage and are expanding our product, engineering, and technical leadership capabilities as we scale our platform, customer base, and enterprise partnerships.

We’re looking for a highly technical and operationally strong Director of QA to lead our quality strategy, QA processes, automation framework, and release-readiness function.

This is a senior quality leadership role for someone who can operate at the intersection of quality engineering, test automation, healthcare technology, platform reliability, AI-enabled product validation, compliance, and engineering execution
.

The ideal candidate has deep experience building and scaling QA practices for complex B2B SaaS platforms and can partner closely with Engineering, Product, Data, AI, Security, Customer Success, and Executive Leadership to ensure we deliver reliable, secure, high-quality products at speed.

This role is U.S.

-based, with preference for candidates working on EST or CST.

The Director of QA will help evolve our QA function into a mature, automation-first, data-driven quality organization that supports rapid product development, enterprise customer expectations, and regulated healthcare environments.

QA Strategy & Leadership

Define and own our overall QA strategy across web applications, backend services, APIs, integrations, data workflows, AI-enabled features, and multi-product platform capabilities.

Build, lead, and scale a QA function that supports multiple engineering teams and product work streams.

Establish quality standards, test strategies, release gates, defect management processes, and QA metrics across the engineering organization.

Partner with Engineering and Product leadership to ensure quality is built into the software development lifecycle from planning through release and production monitoring.

Create a strong quality culture focused on accountability, automation, prevention, and continuous improvement.

Test Automation & Quality Engineering

Design and mature an automation-first QA framework across UI, API, integration, regression, performance, and end-to-end testing.

Increase automated test coverage, reduce manual regression burden, and improve release confidence.

Implement best practices for CI/CD-integrated automated testing, test data management, environment management, and quality reporting.

Evaluate and implement QA tools, frameworks, and processes that improve engineering speed, predictability, and product reliability.

Partner with engineers to ensure testability, maintainability, and quality are considered early in the development process.

Release Readiness & Execution

Own QA readiness for major releases, roadmap commitments, customer launches, integrations, and platform changes.

Partner with engineering teams to identify risks early, prevent escaped defects, and improve delivery predictability.

Drive improvements in defect triage, root cause analysis, regression planning, and production issue prevention.

Ensure release decisions are grounded in clear quality data, risk assessment, and customer impact.

Help teams move faster without compromising quality, security, compliance, or customer trust.

AI & Data Quality

Develop QA strategies for AI-enabled product experiences, including workflow automation, intelligent recommendations, conversational or messaging workflows, decision support, and data-driven product capabilities.

Partner with AI, Data, Product, and Engineering teams to validate model behavior, output quality, guardrails, edge cases, monitoring, feedback loops, and production reliability.

Ensure AI-powered features are tested for accuracy, consistency, safety, usability, explainability, and customer impact.

Support quality processes for data pipelines, integrations, analytics workflows, and customer-facing reporting.

Partner with Engineering and Dev Ops to improve observability, monitoring, incident response, SLOs/SLAs, and production health.

Ensure QA contributes to broader operational maturity, including performance testing, load testing, reliability testing, and failure-mode analysis.

Create clear quality dashboards and metrics around defect trends, automation coverage, release quality, test stability, escaped defects, and customer-impacting issues.

Use data to identify systemic quality risks and drive continuous improvement across engineering teams.

Serve as the senior QA partner to Engineering, Product, Customer Success,…